Title

Authors

Date of this Version

8-2005

Comments

A THESIS Presented to the Faculty of The Graduate College at the University of Nebraska In Partial Fulfillment of Requirements For the Degree of Master of Science, Major: Natural Resource Sciences, Under the Supervision of Professor David A. Wedin. Lincoln, Nebraska: August, 2005

Copyright (c) 2005 Cullen R. Robbins

Abstract

The Bessey Unit of the Nebraska National Forest is a planted ponderosa pine forest located in the Nebraska Sand Hills. Planted in the early 20th Century, it provides a unique opportunity to study the effects of ponderosa pine establishment on the surrounding grassland ecosystem and the effects of increasing pine density on the forest ecosystem. It has been hypothesized that there are key levels of canopy cover at which shifts in ecosystem function occur. The goal of this research was to use remotely sensed data to develop a reliable method for estimating canopy cover. More specifically, canopy cover was estimated by evaluating the relationship between a series of spectral indices applied to data acquired from an AISA overflight of the NNF and measures of vegetation cover (predominantly Leaf Area Index) on the ground. LAI was estimated with a hemispheric camera system and/or a ceptometer in each of eight 40 m x 40 m plots and at each of 97 randomly selected points within the flightline. The hemispheric camera system was shown to be more effective than the ceptometer for measuring LAI in the plots selected for this project. Within these plots, at least three measurements placed approximately 15 meters apart were necessary to capture the range of variability within a plot. The Normalized Difference Vegetation Index (NDVI), Visible Atmospherically Resistant Index (V ARI), Wide Dynamic Range Vegetation Index (WDRVI), and Green Normalized Difference Vegetation Index (GNDVI) all showed a bimodal distribution of pixels and performed well when tested with discriminant function analyses, indicating their potential utility for estimating canopy cover. Ofthe.indices tested, V ARI showed the best correlations with LAI at all but the finest spatial resolution and was sensitive to changes in LAI up to the maximum LAI values observed in ponderosa pine.